Modeling cotton production response to shading in a pecan alleycropping system using CROPGRO

Light optimization assessment in alleycropping systems through model application is becoming an integral part of agroforestry research. The objective of this study was to use CROPGRO-cotton, a process-based model, to simulate cotton (Gossypiumhirsutum L.) production under different levels of light in a pecan (Caryaillinoensis K. Koch) alleycropping system in Jay, Florida, USA. Soil classification in the area was Red Bay sandy loam soil (Rhodic Paleudult). To separate roots of cotton and pecan, polyethylene-lined trenches were installed parallel to tree rows, thus competition for water and nutrients was assumed to be non-existent. Four treatments were set up in the CROPGRO-cotton model, as follows: (1) control (full amount of light transmittance), (2) Row 1 (50% light transmittance), (3) Row 4 (55% light transmittance), and (4) Row 8 (70% light transmittance). Cotton model parameters affecting specific leaf area (SLA), leaf area index (LAI), maximum leaf photosynthetic rate (FLMAX) and carbon partitioning were calibrated using the full sun treatment. Measurements of SLA, LAI, and aboveground biomass were made on the different shaded treatments and compared with simulated values. Simulation results showed that aboveground mechanisms affecting production in shaded environment (i.e., SLA, LAI, LFMAX, and carbon partitioning) influence model behavior. After calibration, the model predicted SLA of cotton in all treatments with reasonable precision. However, LAI was underestimated in the more shaded treatment rows 4 and 8. Generally, the model provided a close agreement between measured and simulated biomass both in 2001 and 2002 (R2 = 0.95 and R2 = 0.92, respectively). In 2001, predicted biomass for the control was 5,401 kg ha−1 compared to the measured value of 5,393 kg ha−1. A similar trend was also observed in 2002. The CROPGRO-Cotton model was able to describe variations in growth among the shaded treatments well across both growing seasons. However, it was found that additional research is needed to improve the model’s ability to simulate LAI under shading conditions. Parameters associated with photosynthesis and dry matter partitioning were reasonably stable across shading treatments and years but those associated with leaf area growth varied.

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